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Building machine learning systems using Python : practice to train predictive models and analyze machine learning results with real use‑cases / Dr Deepti Chopra.

By: Material type: TextTextPublisher: New Delhi : BPB Publications, 2021Edition: 1st editionDescription: 136 pages ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9789389423617
Subject(s): DDC classification:
  • 23 006.3 c.e.b.
Contents:
1. Introduction to Machine Learning ‡ 2. Linear Regression ‡ 3. Classification Using Logistic Regression ‡ 4. Overfitting and Regularization ‡ 5. Feasibility of Learning ‡ 6. Support Vector Machine ‡ 7. Neural Network ‡ 8. Decision Trees ‡ 9. Unsupervised Learning ‡ 10. Theory of Generalization ‡ 11. Bias and Fairness in ML.
Summary: A beginner‑friendly guide to machine learning with practical implementations of regression, classification, clustering, SVM, decision trees, neural networks, and unsupervised learning using Python and scikit‑learn. :contentReference[oaicite:1]{index=1}
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Holdings
Item type Current library Call number Copy number Status Date due Barcode Item holds
Books Books Media and mass communication Library B4 006.3 C.D.B C.1 Available MA0002503
Total holds: 0

Includes bibliographical references.

1. Introduction to Machine Learning ‡ 2. Linear Regression ‡ 3. Classification Using Logistic Regression ‡ 4. Overfitting and Regularization ‡ 5. Feasibility of Learning ‡ 6. Support Vector Machine ‡ 7. Neural Network ‡ 8. Decision Trees ‡ 9. Unsupervised Learning ‡ 10. Theory of Generalization ‡ 11. Bias and Fairness in ML.

A beginner‑friendly guide to machine learning with practical implementations of regression, classification, clustering, SVM, decision trees, neural networks, and unsupervised learning using Python and scikit‑learn. :contentReference[oaicite:1]{index=1}

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